On the general ocean circulation
W. Sturges1975, Reviews of Geophysics
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Abstract
succeeded in modeling seasonal variations, in particular, those of the tropical circulation [Manabe et aL, 1974]. Wetheraid and Manabe [1972] investigated the response of such a model to the seasonal variation of solar radiation, and Houghton et al. [1974], its response to sea surface temperature perturbations. Faegre [1972] and Sellers [1973] have specifically addressed the heat exchange between ocean and atmosphere within these models. Dwyer and Petersen [1973] have addressed the energy transfer through large-scale motion. A statistical dynamic model capable of simulating the seasonal variations in the tropics has been developed by Pike [1972]. The response of the ocean to large-scale surface heat and momentum flux has been investigated by Haney [1974]. Spar [1973a, b] has modeled the effect of ocean surface anomalies on atmospheric circulation, and Haney [1971] has discussed surface thermal boundary conditions of ocean circulation models coupled to the atmosphere. A numerical simulation of the influence of ice conditions on climate was made by Fletcher et aL [1972]. Robinson [1971] presented a general review of climatic models, and Lorenz [1970, 1973] discussed climatic changes as a mathematical problem and their predictability. In this article I will attempt to review some features of the general ocean circulation as they have come into print over the past 4 years. While preparing for this article I became more keenly aware of the truth of the expression 'one man's signal is another man's noise.' There is a clear trend in oceanic studies, not restricted to the past 4 years, to recognize the enormous variability found in the ocean. An important part of this variability, associated with the so-called mesoscale eddies, is discussed in this review series by Robinson. But the 'general ocean circulation,' as
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3 Large-Scale Ocean Circulation: 4 a Dynamical Systems Approach
2005
XXXXXX 75 tal data that has been collected over the last century and 76 one half contributes, in turn, to a more and more 77 complete picture of the climate system's variability. 78 [3] The purpose of the present review paper is to describe 79 the role of the ocean circulation in this variability and to 80 emphasize that dynamical systems theory can contribute 81 substantially to understanding this role. The intended audi-82 ence and the way prospective readers can best benefit from 83 this review are highlighted in Box 1/Appendix A1. To 84 facilitate diverse routes through the paper, we have included 85 a glossary of the principal symbols in Table 1 and a list 86 acronyms in Table 2. 87 1.1. Climate Variability on Multiple Timescales 88 [4] An ''artist's rendering'' of climate variability on all 89 timescales is provided in Figure 1a. The first version of 90 Figure 1a was produced by Mitchell [1976], and many 91 versions thereof have circulated since. Figure 1a is meant 92 to summarize our knowledge of the spectral power S = S w , i.e., the amount of variability in a given frequency band, between w and w + Dw; here the frequency w is the inverse of the period of oscillation and Dw indicates a small increment. This power spectrum is not computed directly by spectral analysis from a time series of a given climatic quantity, such as (local or global) temperature; indeed, there is no single time series that is 10 7 years long and has a sampling interval of hours, as Figure 1a would suggest. Figure 1a includes, instead, information obtained by analyzing the spectral content of many different time series, for example, the spectrum (Figure 1b) of the 335-year long record of Central England Temperatures. This time series is the longest instrumentally measured record of any climatic variable. Given the lack of earlier instrumental records, one can easily imagine (but cannot easily confirm) that the higherfrequency spectral features might have changed, in amplitude, frequency, or both, over the course of climatic history. t1.1 TABLE 1. Glossary of Principal Symbols Symbol Definition Section t1.2 XXXXXX Dijkstra and Ghil: OCEAN CIRCULATION VARIABILITY 3 of 38 XXXXXX 206 eral spectral peaks of variability can be clearly related to 207 forcing mechanisms; others cannot. In fact, even if the 208 external forcing were constant in time, that is, if no 209 systematic changes in insolation or atmospheric composi-210 tion, such as trace gas or aerosol concentration, would 211 occur, the climate system would still display variability 212 on many timescales. This statement is clearly true for the 213 3-7 days synoptic variability of midlatitude weather, which 214 arises through baroclinic instability of the zonal winds, and 215 the ENSO variability in the equatorial Pacific, as discussed 216 above. Processes internal to the climate system can thus 217 give rise to spectral peaks that are not related directly to the 218 temporal variability of the forcing. It is the interaction of 219 this highly complex intrinsic variability with the relatively 220 small time-dependent variations in the forcing that is 221 recorded in the proxy records and instrumental data. 222 1.2. Role of the Ocean Circulation 223 [12] We focus in this review on the ocean circulation as a 224 source of internal climate variability. The ocean moderates 225 climate through its large thermal inertia, i.e., its capacity to 226 store and release heat and its poleward heat transport 227 through ocean currents. The exact importance of the latter 228 relative to atmospheric heat transport, though, is still a 229 matter of active debate [Seager et al., 2001]. The large-230 scale ocean circulation is driven both by momentum fluxes 231 as well as by fluxes of heat and freshwater at the ocean-232 atmosphere interface. The near-surface circulation is dom-233 inated by horizontal currents that are mainly driven by the 234 wind stress forcing, while the much slower motions of the 235 deep ocean are mainly induced by buoyancy differences. 236 [13] The circulation due to either forcing mechanism is 237 often described and analyzed separately for the sake of 238 simplicity. In fact, the wind-driven and thermohaline circu-239 lation together form a complex three-dimensional (3-D) 240 flow of different currents and water masses through the 241 global ocean. The simplest picture of the global ocean 242 circulation has been termed the ''ocean conveyor'' [Gordon, 243 1986; Broecker, 1991]; it corresponds to a two-layer view 244 where the vertical structure of the flow field is separated 245 into a shallow flow, above the permanent thermocline at 246 roughly 1000 m, and a deep flow between this thermocline 247 and the bottom (i.e., between a depth of roughly 1000 m and 248 4000 m); see Figure 2. The unit of volume flux in the ocean 249 is 1 Sv = 10 6 m 3 s À1 , and it equals approximately the total 250 flux of the world's major rivers. MacDonald and Wunsch 251 [1996] and Ganachaud and Wunsch [2000] have provided 252 an updated version of this schematic representation of the 253 ocean circulation. 254 [14] In the North Atlantic, for instance, the major current 255 is the Gulf Stream, an eastward jet that arises through the 256 merging of the two western boundary currents, the north-257 ward flowing Florida Current and the southward flowing 258 Labrador Current. In the North Atlantic's subpolar seas, 259 about 14 Sv of the upper ocean water carried northward by 260 the North Atlantic Drift, the northeastward extension of the 261 Gulf Stream, is converted to deepwater by cooling and 262 salinification. This North Atlantic Deep Water (NADW) XXXXXX Dijkstra and Ghil: OCEAN CIRCULATION VARIABILITY 4 of 38 XXXXXX 263 flows southward, crosses the equator, and joins the flows 264 in the Southern Ocean. The outflow from the North 265 Atlantic is compensated by water coming through the 266 Drake Passage (about 10 Sv) and water coming from the Indian Ocean through the Agulhas Current system (about 268 4 Sv). Part of the latter ''Agulhas leakage'' may originate 269 from Pacific water that flows through the Indonesian 270 Archipelago. We refer to earlier reviews [Gordon, 1986; 271 Schmitz, 1995; World Ocean Circulation Experiment 272 (WOCE), 2001] for more complete information on the 273 circulation in each major ocean basin as well as from one 274 basin to another. 275 [15] Changes in the ocean circulation can influence 276 climate substantially through their impact on both the 277 meridional and zonal heat transport. This can affect mean 278 global temperature and precipitation, as well as their distri-279 bution in space and time. Subtle changes in the North Atlantic surface circulation and their interactions with the 281 overlying atmosphere are thought to be involved in climate 282 variability on interannual and interdecadal timescales, as 283 observed in the instrumental record of the last century 284 [Martinson et al., 1995; Ghil, 2001]. Changes in the 285 circulation may also occur on a global scale, involving a 286 transition to different large-scale patterns. Such changes 287 may have been involved in the large-amplitude climate 288 variations of the past [Broecker et al., 1985]. 289 1.3. Modeling Hierarchy 290 411 Those fixed points for which eigenvalues with s r > 0 exist 412 are unstable, since the perturbations are exponentially 413 growing. Fixed points for which all eigenvalues have s r < 0 414 are linearly stable. 415 [27] Discretization of the systems of partial differential 416 equations (PDEs) that govern oceanic and other geophysical 417 flows [Gill, 1982; Pedlosky, 1987, 1996] leads to a system 418 of ODEs (1), with large n. In many cases the linearization 419 (3)-(5) yields solutions that are the classical linear waves of 420 geophysical fluid dynamics. These include neutrally stable 421 waves, like Rossby or Kelvin waves, or unstable ones, like 422 those associated with the barotropic or baroclinic instability 423 of ocean currents. 424 [28] If the number of solutions or their stability prop-425 erties change as a parameter is varied, a qualitative 426 change occurs in the behavior of the dynamical system: 427 The system is then said to undergo a bifurcation. The 428 points at which bifurcations occur are called bifurcation 429 points or critical points. A bifurcation diagram for a 430 particular system (1) is a graph in which the variation 431 of its solutions is displayed in the phase-parameter space. 432 Information on the most elementary bifurcations is pre-433 sented in Box 2/Appendix A2. 434 [29] Bifurcation theory goes beyond classical, linear 435 analysis in studying the nonlinear saturation of and inter-436 actions between linear instabilities. When the interaction
Variability of the tropical oceans
Dynamics of Atmospheres and Oceans, 1979
The Representation of Ocean Circulation and Variability in Thermodynamic Coordinates
Journal of Physical Oceanography, 2014
The ocean's circulation is analyzed in Absolute Salinity S A and Conservative Temperature Q coordinates. It is separated into 1) an advective component related to geographical displacements in the direction normal to S A and Q isosurfaces and 2) into a local component, related to local changes in S A -Q values, without a geographical displacement. In this decomposition, the sum of the advective and local components of the circulation is equivalent to the material derivative of S A and Q. The sum is directly related to sources and sinks of salt and heat. The advective component is represented by the advective thermohaline streamfunction C adv SAQ . After removing a trend, the local component can be represented by the local thermohaline streamfunction C loc SAQ . Here, C loc SAQ can be diagnosed using a monthly averaged time series of S A and Q from an observational dataset. In addition, C adv SAQ and C loc SAQ are determined from a coupled climate model. The diathermohaline streamfunction C dia SAQ is the sum of C adv SAQ and C loc SAQ and represents the nondivergent diathermohaline circulation in S A -Q coordinates. The diathermohaline trend, resulting from the trend in the local changes of S A and Q, quantifies the redistribution of the ocean's volume in S A -Q coordinates over time. It is argued that the diathermohaline streamfunction provides a powerful tool for the analysis of and comparison among ocean models and observation-based gridded climatologies.
A global survey of ocean-atmosphere interaction and climate variability
Geophysical Monograph Series, 2000
The interaction of the ocean and atmosphere plays an important role in shaping the climate and its variations. This chapter reviews the current state of knowledge of air-sea interaction and climate variations over the global ocean. The largest source of climate variability in the instrumental record is El Niño-Southern Oscillation (ENSO), which extends its reach globally through the ability of the atmosphere to bridge ocean basins. The growth of ENSO owes its existence to a positive ocean-atmosphere feedback mechanism (originally envisioned by J. Bjerknes) that involves the interaction of ocean dynamics, atmospheric convection, and winds in the equatorial Pacific. The Bjerknes feedback and the resultant equatorial zonal mode of climate variability are a common feature to all three tropical oceans despite differences in dimension, geometry and mean climate. In addition to this zonal mode, the tropics also support a meridional mode, whose growth is due to a thermodynamic feedback mechanism involving the interaction of the cross-equatorial gradient of properties such as sea surface temperature and displacements of the seasonal intertropical convergence zone. This meridional mode is observed in the tropical Atlantic, with some evidence of its existence in the Pacific and Indian Oceans. In the extratropics, in contrast, the sources of climate variability are more distributed. Much of climate variability may be explained by the presence of white noise due to synoptic weather disturbances whose impact on climate at longer timescales is due to the integrating effect of the ocean's ability to store and release heat. Still, there is some evidence of a more active role for the mid-latitude ocean in climate variability, especially near major ocean currents/fronts. Finally, various atmospheric and oceanic bridges that link different ocean basins are discussed, along with their implications for paleoclimate changes and the current global warming.
Fine-scale variability at 140°W in the equatorial Pacific
Journal of Geophysical Research, 1986
In November-December 1984 we carried out an intensive 12-day upper ocean sampling program on the equator at 140øW as part of the Tropic Heat Experiment. From our observations we constructed hourly averaged profiles of temperature, salinity, at, turbulent kinetic energy dissipation rate, and horizontal velocity. These data were used to examine the correspondence between hydrographic and velocity fields and to compare the measured turbulent dissipations with the calculated Richardson numbers. We found that the core of the Equatorial Undercurrent tracked a density surface (a t = 25.25) on times as short as 1 hour. The variability in both hydrographic and velocity fields was greatest at the semidiurnal frequency. The supertidal energy was not significantly different from the Garrett-Munk mid-latitude level once latitudinal scaling was removed from the Garrett-Munk model parameters. Horizontal velocity spectra were found to be contaminated by displacement of the background shear. Turbulent dissipation was dominated by a dirunal cycle, with high values of dissipation occurring at night above the undercurrent core. Shear and buoyancy frequency, calculated over 12-m vertical scales, were observed to track each other above the core and were dominated by a diurnal period above 40 m and by a semidiurnal period below 40 m. When shear and buoyancy frequency were combined to form a Richardson number, neither diurnal nor semidiurnal cycles were present. Above the undercurrent core, the Richardson numbers were uniformly small (0.3 to 0.6). 1. INTRODUCTION Studies have suggested that space and time variability in the equatorial ocean may be quite different from variability at mid-latitudes. Internal wave spectra from the equatorial Indian Ocean indicate more energy at frequencies above the tidal than is predicted by the Garrett-Munk (GM) universal internal wave spectrum [Eriksen, 1980]. Other deviations from GM [Garrett and Munk, 1972, 1975] include less spatial coherence [Wunsch and Webb, 1979; Eriksen, 1980] and an excess of horizontal kinetic energy over potential energy at subtidal frequencies [Eriksen, 1980]. One obvious difference is that at the equator there is no Coriolis parameter to limit the frequency bandwidth of internal waves. From their fine-structure measurements, Toole and Hayes [1984] found enhanced shear and strain variance and a greater proportion of low values of the Richardson number on the equator. McPhaden [1985] noted anomalously high fine-scale temperature and density variance confined within 1 ø of the equator. Microstructure measurements indicated a peak in turbulent kinetic energy dissipation rate within 1 ø of the equator [Crawford, 1982], but more recent results [Moumet al., 1986b-I have shown this peak to be an artifact of the sampling limitations of the previous study. In November-December 1984 we carried out an intensive 12-day sampling program near the equator at 140øW as part of the Tropic Heat experiment. Vertical profiles of temperature, conductivity, and small-scale shears were obtained every 10 min (on average) with the rapid sampling vertical Copyright 1986 by the American Geophysical Union. Paper number 6C0326. 0148-0227/86/006C-0326505.00 profiler (RSVP). Vertical profiles of horizontal currents were obtained every 30 s with a shipboard acoustic Doppler current profiler (ADCP). From these data we constructed hourly averaged profiles of temperature T, salinity S, at, kinetic energy dissipation rate e, and horizontal velocity. Using these series of profiles we made the following observations and comparisons: 1. We examined the correspondence between hydrographic and velocity fields. We found that the core of the Equatorial Undercurrent (EUC) tracked a density surface (a t = 25.25) on times as short as 1 hour. The core tracked the salinity maximum almost as well. 2. We compared the high-frequency variability with that observed at other latitudes in terms of the Garrett-Munk model. We found that (1) the time variability in both hydrographic and velocity fields was greatest at the semidiurnal frequency, (2) the supertidal energy was not significantly different from the Garrett-Munk mid-latitude level once the latitudinal scaling was removed from the Garrett-Munk model parameters, and (3) the horizontal velocity spectra were contaminated by displacement of the background shear. 3. We compared calculated Richardson numbers with the observed values of turbulent kinetic energy dissipation rate and found that (1) the dissipation was dominated by a diurnal cycle, with high values occurring at night above the undercurrent core, (2) shear and buoyancy frequency calculated over 12-m scales tracked each other extremely well, with a diurnal cycle above 40 m and a semidiurnal cycle below 40 m and (3) the Richardson number was uniformly small (between 0.3 and 0.6) above the undercurrent core. For the 12-day period, the Richardson number displayed neither a diurnal nor a semidiurnal periodicity. (In longer times series, periods were observed when the Richardson number cycled diurnally near the surface.) 12,887 12,888
Stochastic Forcing of the North Atlantic Wind-Driven Ocean Circulation. Part I: A Diagnostic Analysis of the Ocean Response to Stochastic Forcing
Journal of Physical Oceanography, 2006
As discussed in Part I of this study, the magnitude of the stochastic component of wind stress forcing is comparable to that of the seasonal cycle and thus will likely have a significant influence on the ocean circulation. By forcing a quasigeostrophic model of the North Atlantic Ocean circulation with stochastic wind stress curl data from the NCAR CCM3, it was found in Part I that much of the stochastically induced variability in the ocean circulation is confined to the western boundary region and some major topographic features even though the stochastic forcing is basinwide. This can be attributed to effects of bathymetry and vorticity gradients in the basic state on the system eigenmodes. Using generalized stability theory (GST), it was found in Part I that transient growth due to the linear interference of nonnormal eigenmodes enhances the stochastically induced variance. In the present study, the GST analysis of Part I is extended and it is found that the patterns of wind stress curl that are most effective for inducing variability in the model have their largest projection on the most nonnormal eigenmodes of the system. These eigenmodes are confined primarily to the western boundary region and are composed of long Rossby wave packets that are Doppler shifted by the Gulf Stream to have eastward group velocity. Linear interference of these eigenmodes yields transient growth of stochastically induced perturbations, and it is this process that maintains the variance of the stochastically induced circulations. Analysis of the large-scale circulation also reveals that the system possesses a large number of degrees of freedom, which has significant implications for ocean prediction. Sensitivity studies show that the results and conclusions of this study are insensitive and robust to variations in model parameters and model configuration.
Mechanisms of interdecadal climate variability and the role of ocean–atmosphere coupling
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Climate variability and mid-latitude mechanisms of ocean-atmosphere interactions are investigated with coupled and uncoupled integrations of a threedimensional ocean-atmosphere-land-ice climate model of intermediate complexity. We focus on the decadal and interdecadal variability of the system and give a statistical and dynamical description of its oceanic and atmospheric signatures. In our coupled control integration, an oceanic oscillation of a period of around 20 years is found to be associated with variability of the meridional overturning circulation and is manifested by surface anomalies of temperature and salinity. On such timescales the oceanic oscillation is able to imprint itself on the atmosphere, which then covaries with the ocean at the oscillation period. The essentially slaved atmospheric pattern helps maintain the oceanic oscillation by providing large-scale anomalous heat fluxes, so catalyzing the oscillation. That is to say, because the atmosphere covaries with the ocean the damping felt by the ocean is less than what would be felt with a fixed atmosphere, so broadening the parameter regime over which such variability occurs. In addition to the presence of an atmosphere, the period and amplitude of the oscillation are found to be influenced both by the oceanic vertical diffusivity j v , by geometrical factors, and by the presence of stochastic heat fluxes. In general, oscillations occur most readily for large values of j v , when the mean state of the ocean is characterized by a strong meridional overturning circulation. If j v is sufficiently strong, the ocean will oscillate even in the absence of a dynamical atmosphere. However, for more realistic values of j v , the presence of an interacting atmosphere is required for significant oscillations. If the ocean is forced by imposed stochastic heat fluxes, instead of a fully interacting atmosphere, then decadal-scale oscillations can be produced suggestive of a damped oscillator. However, the parameter range over which oscillations occur is smaller than when the ocean is coupled to full atmosphere. More generically, the ability of comprehensive coupled oceanatmosphere models to produce multi-decadal variability, realistic or otherwise, will depend on the oceanic mean state, and so on the diapycnal diffusivity of the modelled ocean, as well as on the ability of the atmosphere to reduce the damping felt by the ocean and so on the atmosphere's ability to respond to persistent sea-surface temperature anomalies.
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